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<table width="100%" summary="page for USFinanceIndustry"><tr><td>USFinanceIndustry</td><td style="text-align: right;">R Documentation</td></tr></table>

<h2>
US Finance Industry Profits
</h2>

<h3>Description</h3>

<p>A <code>data.frame</code> giving the profits of 
the finance industry in the United States 
as a proportion of total corporate domestic 
profits.
</p>


<h3>Usage</h3>

<pre>data(USFinanceIndustry)</pre>


<h3>Format</h3>

<p> A <code>data.frame</code> with the following columns:
</p>

<dl>
<dt>year</dt><dd><p> integer year starting with 1929 </p>
</dd>
<dt>CorporateProfitsAdj</dt><dd>
<p>Corporate profits with inventory valuation and capital
consumption adjustments in billions of current (not adjusted for
inflation) US dollars
</p>
</dd>
<dt>Domestic</dt><dd><p> Domestic industries profits in billions </p>
</dd>
<dt>Financial</dt><dd><p> Financial industries profits in billions </p>
</dd>
<dt>Nonfinancial</dt><dd><p> Nonfinancial industries profits in billions </p>
</dd>
<dt>restOfWorld</dt><dd>
<p>Profits of the &quot;Rest of the world&quot; in their contribution to US
Gross Domestic Product in billions
</p>
</dd>
<dt>FinanceProportion</dt><dd><p> = Financial/Domestic </p>
</dd>
</dl>



<h3>Details</h3>

<p>This is extracted from Table 6.16 of the 
National Income and Product Accounts (NIPA) 
compiled by the Bureau of Economic Analysis 
of the United States federal government.  
This table comes in four parts, A (1929-1947), 
B (1948-1987), C (1987-2000), and D 
(1998-present).  Parts A, B, C and D contain 
different numbers of data elements, but the
first five have the same names and are the 
only ones used here.  The overlap between 
parts C and D (1998-2000) have a root mean 
square relative difference of 0.7 percent;  
there were no differences between the numbers 
in the overlap period between parts B and C 
(1987).
</p>
<p>This was created using the following command:
</p>
<p><code>demoDir &lt;- system.file('demoFiles', package='Ecdat')</code>
<code>demoCsv &lt;- dir(demoDir, pattern='csv$', full.names=TRUE)</code>
</p>
<p><code>nipa6.16 &lt;- readNIPA(demoCsv)</code>
<code>USFinanceIndustry &lt;- as.data.frame(nipa6.16)</code>
<code>names(USFinanceIndustry) &lt;- c('year', 
    'CorporateProfitsAdj', 'Domestic', 'Financial', 
    'Nonfinancial', 'restOfWorld')</code>
<code>USFinanceIndustry$FinanceProportion &lt;- 
    with(USFinanceIndustry, Financial/Domestic)</code>
</p>


<h3>Source</h3>

<p><a href="http://www.bea.gov">http://www.bea.gov</a>:  Under &quot;U.S. Economic Accounts&quot;, first
select &quot;Corporate Profits&quot; under &quot;National&quot;.  Then next to
&quot;Interactive Tables&quot;, select, &quot;National Income and Product Accounts
Tables&quot;.  From there, select &quot;Begin using the data...&quot;.  Under
&quot;Section 6 - income and employment by industry&quot;, select each of the
tables starting &quot;Table 6.16&quot;.  As of February 2013, there were 4 such
tables available:  Table 6.16A, 6.16B, 6.16C and 6.16D.  Each of the
last three are available in annual and quarterly summaries.  The
<code>USFinanceIndustry</code> data combined the first 4 rows of the 4
annual summary tables.
</p>


<h3>See Also</h3>

<p><code>readNIPA</code>
</p>


<h3>Examples</h3>

<pre>
data(USFinanceIndustry)
plot(FinanceProportion~year, USFinanceIndustry, type='b',
     ylim=c(0, max(FinanceProportion, na.rm=TRUE)),
     xlab='', ylab='', las=1, cex.axis=2, bty='n', lwd=2,
     col='blue')

# Write to a file for Wikimedia Commons
## Not run: 
if(FALSE){
  svg('USFinanceIndustry.svg')
  plot(FinanceProportion~year, USFinanceIndustry, type='b',
     ylim=c(0, max(FinanceProportion, na.rm=TRUE)),
     xlab='', ylab='', las=1, cex.axis=2, bty='n', lwd=2,
     col='blue')
  dev.off()
  }
  
## End(Not run)
</pre>


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